JISTEM J.Inf.Syst. Technol. Manag. vol.14 número3

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Journal of Information Systems and Technology Management – Jistem USP Vol. 14, No. 3, Sep/Dec., 2017 pp. 439–461

ISSN online: 1807-1775

DOI: 10.4301/S1807-17752017000300009

Published by TECSI FEA USP, Brazil – 2017 www.jistem.fea.usp.br

Manuscript irst received: 2017/Aug/21. Manuscript accepted: 2017/Dec/15

Amarolinda Zanela Klein, Full Professor, Post Graduate Program in Management, Unisinos Business School, Unisinos University, Brazil. E-mail: aczanela@unisinos.br

Fabiana Beal Pacheco, Master in Management, Unisinos University, Brazil. E-mail: fabiana.beal@gmail.com

Rodrigo da Rosa Righi, Professor and Coordinator of the Post Graduate Program in Applied Computer Sciences, Unisinos University, Brazil. E-mail: rrrighi@unisinos.br

INTERNET OF THINGS-BASED PRODUCTS/SERVICES: PROCESS AND CHALLENGES ON DEVELOPING THE BUSINESS MODELS

Amarolinda Klein https://orcid.org/0000-0001-8585-9057

Business School, Unisinos University, RS, Brazil

Fabiana Beal Pacheco https://orcid.org/0000-0003-0949-9111

Rodrigo da Rosa Righi https://orcid.org/0000-0001-5080-7660

Polytechnic, Unisinos University, RS, Brazil

ABSTRACT

Many companies nowadays are struggling to understand the unprecedented complexity of developing business models for products and services based on the Internet of Things (IoT). This article aims at investigating what are the elements to be taken into account in order to create a business model for IoT-based products/services and what are the main challenges faced in this process. To address these questions, we review the literature on the creation of business models for the IoT and we analyze data from an action research involving the generation of a business model for an IoT-based product - a smart door lock – in a small company. We explore how this process occurred and the challenges faced.

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www.jistem.fea.usp.br INTRODUCTION

The technologies of the Internet of Things (IoT) are increasingly embedded in previously non-digital products of everyday life, which impacts the nature of goods and services, and, in consequence, on overarching business models (Yoo et al., 2012, Turber & Smiela, 2014; Weinberger et al., 2016). The separation between physical and digital industries is now consigned to the past because the IoT makes possible hybrid solutions that merge physical products and digital services (Fleisch et al., 2014).

The concept of IoT surpasses several areas of knowledge and can be considered as potentially relevant in any supply chain, creating unprecedented opportunities in the public and private sectors to develop new products and services, increase productivity and process eiciency, improve decision making, solve critical social problems and develop new user experiences (Borgia, 2014; Barrett et al., 2015, Yoo et al., 2012). Perera et al. (2015) present a broad view and concrete examples of IoT applications in several domains of private and public sectors.

IoT-based products/services allow for a radical change in existing business models (Porter & Heppelmann, 2014). However, a mediocre technology used in a great business model can be better than a great technology explored in a poor business model (Chesbrough, 2010); therefore, we must understand how to generate proper business models for IoT-based products and services (Dijkman et al., 2015; Turber & Smiela, 2014; Weinberger et al., 2016).

Nevertheless, still little is known about how the IoT change business models; the larger literature stream is focused on technical IoT challenges and few empirical studies investigate IoT-speciic business model innovations in detail (Diaz, Muñoz & Gonzáles, 2017); most of the studies on this subject only provide anecdotal evidence and do not base their indings on empirical data (Bilgeri & Wortmann, 2017). In sum, regardless the fast technical progress of IoT technologies, the business and management literature do not explicitly consider the logic of digitized business environments based on it (Turber & Smiela, 2014; Leminen et al., 2015; Zhang & Wen, J., 2016) and how business models for the IoT should be constructed (Dijkman et al., 2015). Reviewing the literature, as we are going to show in section 4, one can ind a set of works on the creation of business models for the IoT, but there are two clear pitfalls in these works: (1) most of them are not based on empirical research in organizations and; (2) most of them are based on general business models frameworks, such as the Business Model Canvas (BMC).

The IoT brings numerous opportunities for products and services innovations and, at the same time, it brings a set of uncertainties, for example, it can increase the complexity and the level of competition in most manufacturing systems (Ehret & Wirtz, 2017). It is key to understand what can be gained by connecting current products to the IoT and not simply doing it because the IoT is a hype (Saarikko, Westergren, & Blomquist, 2017).

Therefore, this article aims at investigating two research questions: (1) what are the elements to be considered to create a business model for IoT-based products/services? (2) What are the main challenges faced in this process? To address these questions, we review the literature on business models for the IoT and we analyze data from an action research involving the generation of a business model for an IoT-based product - a smart lock – in a small company. We explore how this process occurred and the challenges faced.

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main challenges faced during the process of business modelling for the IoT-based product are discussed; they are related to six main categories: (1) the IoT ecosystem (2) the product/service development, (3) the value proposition, (4) the irm’s internal capabilities (5) the technology infrastructure, (6) the generation of revenues.

The remainder of this article presents its key theoretical concepts, the literature review on business models for the IoT, followed by the research method, the action research results, and discussion. Finally, we present a conclusion section that highlights the article’s contributions and we point out some questions that can be addressed in future research.

THE INTERNET OF THINGS (IOT)

The IoT refers to an emerging paradigm consisting of a continuum of uniquely addressable things communicating to one another to form a worldwide dynamic network (Koreshof et al., 2013; Borgia, 2014). According to Mattern and Floerkemeier (2010), the IoT is not the result of a single technology, but it is the combination of several complementary development technologies that provide capabilities, which help to bridge the gap between the virtual and the physical world. These capabilities include (Mattern & Floerkemeier, 2010; Porter & Helpperman, 2014):

Communication and cooperation – in the IoT the objects have the ability to network with

Internet resources and with each other, to make use of data and services and update their state; they use several wireless technologies for it, such as 4G, Wi-Fi, Bluetooth, ZigBee, Wireless Personal Area Networks (WPANs), among others.

Addressability - the objects are located on the Internet of Things and can be remotely conigured

and addressed via discovery, look-up or name services; they can be remotely interrogated or conigured.

Identiication - the objects are uniquely identiied, using technologies such as RFID (Radio Frequency Identiication) and NFC (Near Field Communication). Identiication enables objects to be linked to speciic information associated with them.

Context-aware sensing – in the IoT the objects collect data about their surrounding environment

with the use of sensors, they record and forward data and react according to the context;

Monitoring – sensors enable the monitoring of a product’sproduct’s condition, the product’s

operation, and usage; it also enables alerts and notiications of changes.

Actuation - the objects contain actuators that can be used to remotely control real-world processes in the environment via the Internet (for example, converting electrical signals into mechanical movements);

Embedded information processing - the smart objects have microcontrollers or processors,

and storage capacity. These resources can be used, for instance, to process and interpret sensor’s information, or to give products a ““memory”” of how they are used.

Localization - the smart objects know their physical location and can be located via the use of

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User interface - the objects can communicate with people by means such as l exible displays,

image or gesture recognition. Innovative interaction forms are relevant because the IoT must provide natural interfaces with users.

All these capabilities that result from the integration of the IoT technologies generate a wide range of possibilities to create innovative products and services with aggregate value, connecting the physical and the digital worlds (Borgia, 2014). Servitization is here dei ned as the act of adding value to a company’s core of erings through services (Vandermerwe & Rada, 1988) is a key concept to the IoT because all the technological infrastructure and data collected must result in innovative services that can be associated with traditional physical products, as exemplii ed in Figure 1.

Figure 1. Innovation and value proposition with the IoT

Source: Created by the authors, based on Fleisch, Weinberger & Wortmann (2014) and Perera et al. (2015)

As illustrated in Figure 1, a traditional object (such as a door lock – as we are going to discuss later in this article) is transformed (through IoT technologies) into a smart object that can collect and transmit contextual data, that can be used to generate services – it is not a “dumb” door lock anymore; it can be a key component of a security system (for example). Therefore, the IoT can allow i rms to of er packages of customer-focused combinations of goods, services, support, self-service, and knowledge, with a servitization logic (Vandermerwe & Rada, 1988)

Infrastructure and value creation with the Internet of Things (IoT)

Level 1 Traditional objects Level 2 “aware” and “active” objects Level 3 Connected objects (to other

objects or to people) Level 4 Relevant information is generated Level 5 New services with aggregate value

The smart door lock detects movement, checks ID and opens

the doors The smart door lock

is connect to a smartphone Digital services Analytics Connection Physical objects Sensors/ actuators Door lock Digital/ Global D ig it a l Wo rl d Value proposition P h y si ca l Wo rl d

Number of entrants, access time Security services in the

face of home invasion

• Sensors • Actuators • RFID • GPS • Bluetooth • Wifi • WLAN • Cloud • NFC

• 4G, 5G

• Big Data

• Datamining • Analytics Several platforms Physical/ Local Analytics Technologies Examples Physical/ Levels

The smart door lock

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This transformation demands to rethink the business model of IoT-based product/services, to proit from innovation.

BUSINESS MODELS

The business model literature has its origins in the late 1990’s (Timmers, 1998). Since then, there has been an increasing interest in this topic in practice and various research areas (Osterwalder & Pigneur, 2009). For Zott, Amit and Massa (2011), business models have been used to address or explain the e-business phenomenon and the use of IT in organizations, as well as the management of technology and innovation. Companies must understand how to unlock value from technology, which has stimulated research on this concept (Timmers, 1998; Ehret & Wirtz, 2017).

Zott, Amit and Massa (2011) claim, after an extensive literature review, that a business model has diferent deinitions: it can be referred as a statement, a description, a representation, an architecture, a tool or a conceptual model, a structural template, a method, a framework, a pattern, or a set of elements. A business model can be deined as a bundle of speciic activities conducted to satisfy the perceived needs of the market, along with the speciication of which parties (a company and its partners) perform the activities, and how these activities are linked to each other (Amit & Zott, 2012). According to Turber and Smiela (2014), a business model is a holistic representation of a business formed by the combination of internal and external factors. There is no consensus on the elements that compose a business model. Timmers (1998:4) claims that a business model has to indicate (1) an architecture for the product, service and information lows (2) a description of the various business actors and their roles; (3) the potential beneits for the business actors; and (4) the sources of revenues. Gassmann, Frankenberger and Csik (2013) indicate that it must set the target customer, the value proposition to meet customer’s needs, the value chain necessary to deliver the value proposition and inally the revenue model used to capture the value. Dmitriev et al. (2014) reviewed the literature, indicating that the most frequently identiied elements in business models are: value proposition, target market, revenue model, partner network, internal infrastructure, and processes. Rethinking and reconiguring them constitutes a highly complex and transversal management task.

There are various business model frameworks, at the enterprise level and at the industry level (Sun et al., 2012; Leminen et al. 2012). At the enterprise level, the most used frameworks are: the Value Chain, the Strategy Map, the Four-Box Business Model, and the Business Model Canvas (BMC). At the industry level, one can consider: the Five Forces, the Value Net, Supply Chain models, and the Business Model Environment. Among these models, the Value Chain and the BMC are the most widely used (Sun et al., 2012). In the next section, we analyze the state of art of business models for the IoT.

BUSINESS MODELS FOR THE IOT: WHAT WE KNOW SO FAR

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and purely technical articles, as well as repeated articles (located in diferent databases). In total, we selected 64 articles, and, after reading them through their abstracts and overview, 24 were selected and read thoroughly, leading to the search for other 9 articles cited by them. The 33 articles in total were saved in an NVivo® database and analyzed through their classiication data (date, type of publication, source, method, etc.) and content. We codiied the information on the goals of each article, the theoretical foundation of the IoT business models discussed or proposed by them, and also the challenges for the creation of business models for the IoT presented – see the data about the selected articles in Table 1.

As we can observe at Table 1, there are several approaches on business models for the IoT, considering diferent concepts, models, and frameworks, including: the Laws of information (1); Resource-based Perspective (1); Entrepreneurship and Transaction Cost Theories, High-resolution management (2), Service Dominant logic (3), Product Portfolio, Business Ecosystems literature (4), the St. Gallen Business Model Navigator (3), Supply chain analysis (1), Five competitive forces (1) Scenarios Models (1), Analytic Network Process (ANP) (1), Innovation stages (1) and Pricing models (1). There are two main approaches considered: the BMC (7) and Value models (6).

Most of the papers focus on the value proposition and competitive gains related to the IoT (such as Porter & Heppelmann, 2014), forms of generating revenues from the IoT (Fleisch et al., 2014), while others focus on a broader view of the business model components, using, for instance, the BMC (such as Buchener & Uckelmann, 2011 and Dijkman et al., 2015) while others expand the business model not only to a single organization but to the IoT ecosystem (like Leminen et al., 2012 and 2015 and Saarikko, Westergren, & Blomquist, 2017).

The variety of approaches to IoT business models in the literature and the use of “generic” business model frameworks can be related to two factors: (a) it is a recent research subject; the articles started to be published in 2011; 19 of them were published in academic journals, the others in conferences (7), and the remaining in book chapters or public reports (b) the IoT is a complex phenomenon, as we are going to discuss later, which brings a set of challenges to business modelling. However, it is important to highlight that the majority of works (19) are theoretical papers. Most of the papers that perform some empirical research use only illustrative cases, scenarios or experts interviews and perceptions surveys on the subject to create or validate their proposed frameworks for IoT business modeling; none of them presents data on the process of business modeling for the IoT in a real company.

Even so, these works indicate several challenges related to developing business models for the IoT. We analyzed these challenges (via open codiication) and classiied them into 6 categories: value proposition, product/service development, technology infrastructure, ecosystems, irm’s internal capabilities and revenues, as shown in Table 2.

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Table 1. Articles on business models for IoT.

Author(s) Year Goal Method Theory/Literature

Bilgeri and Wortmann 2017 Investigates speciic barriers to technology-driven IoT business model

innovation Interviews Innovation stages

Buchener and Uckelmann 2011 Discusses the Internet of Things from an economic perspective,

based on the business model concept. Theoretical paper

Laws of information and B.M.Canvas

Chan 2015 Proposes a business model for IoT that consists of three dimensions: _{“Who, Where, and Why”} Case Studies Previous business models for IoT

Diáz, Munhòz and

Gonzáles 2017 Business models of public services provided with the IoT and other technologies in smart cities

Case studies (8) BMC

Dijkman et al 2015 Presents a business model framework speciic for IoT applications Survey BMC

Ehret and Wirtz 2016 Explores the conditions for designing nonownership business models _{for the emerging IIoT (Industrial Internet of Things)} Theoretical paper Entrepreneurship and Transaction Cost Theories

Ehret and Wirtz 2017 Explores the conditions for designing nonownership business models

for the emerging IoT Theoretical paper

Entrepreneurship and Transaction Cost Theories

Fleisch et al 2014 Derive general business model logic for the Internet of Things and _{some speciic components and patterns for business models} Theoretical paper

HRM, Service-dominant

logic/St. Gallen Business

Model Navigator

Gerpott and May 2016

Provides a foundation for irms trying to evaluate the suitability of IoT-enhanced oferings against the background of their current

portfolio.

Theoretical paper Product portfolio

Ghanbari et al. 2017 Discuss the relevance of vertical cooperation in the IoT and highlight

the need to develop new value networks that leverage this cooperation Theoretical paper Value Chain

Glova et al 2014

Applies an originally value-based requirement technique, e3-value, to model value creation and value exchange within an e-business

network of multiple business actors Theoretical paper Value Model (e3-value)

Hognelid and Kalling 2015 Analyzes the impact of IoT on business models and sources of value _{creation by applying a proposed framework to empirical illustrations.} Theoretical paper

Value creation for e-business

and Porter & Heppelmann’s

IoTcapabilities

Ju et al 2016 Develops a generic business model framework for IoT, based on _{BMC, through literature analysis and interviews.} Interviews, Case Studies BMC

Keskin and Kennedy 2015

Addresses the need for e-Commerce service models in an IoT-enabled industry by deining players and predicting possible states in which a

irm can choose to do business Theoretical paper

Multi-sided markets and

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Leminen et al. 2012 Discusses how the technological advancements and convergence with _{IoT shape and afect IoT businesses and dynamic IoT ecosystems.} Theoretical paper BMC

Leminen et al. 2015 Investigates ecosystem business models or “value designs” in the_{IoT ield.} Delphi and Interviews Value design, ecosystems

Li et al. 2012

Provides a theoretical framework which classiies IoT strategies into four archetypes from two dimensions of managers’ strategic intent

and industrial driving forces Theoretical paper

Resource-based Perspective and IS perspective

Li and Xu 2013 Proposes a business model for IoT-based on concepts of MOP (Multiple _{Open Platforms)} Theoretical paper MOP and business models literature

Novales et al. 2016 Provides an overview of the diferent terms and identiies ive _{conceptual elements that form the building blocks of digitized products} Systematic literature _review Literature on digitized products

Niyato et al. 2015 Proposes a new pricing scheme for IoT service providers Theoretical paper Pricing models

Porter and Heppelman 2014 Deconstructs the smart, connected products revolution and explore its

strategic and operational implications. Theoretical paper Five competitive forces

Qin and Yu 2015 Studies the Value Net Model and the elements of the business model

for IoT for telecom operators. Theoretical paper Value Net Model

Rong et al. 2015 Investigates how IoT could lead to a co-evolving business ecosystem

rather than a supply chain. Case Study

Business ecosystems (3c 36 model)

Saarikko, Westergren, and

Blomquist

2017 Discuss value creation with the IoT and the need to form partnerships

to develop intricate solutions Case studies (3) Value creation/value chain

Sun et al 2012 Proposes the Business DNA Model - a representation of a business

model regarding Design, Needs, and Aspirations. Theoretical paper BMC

Tesch 2016 Discusses scenario planning as a means for evaluating business models

in the IoT context. Design Research BMC and Scenarios

Turber and Smiela 2014 Describes the design and evaluation of a model to capture, visualize _{and analyze irms’ current and future business models in IoT.} Design Research St Gallen business navigator/_{dominant service logic}

Turber et al. 2014 Addresses the need for a business model framework in IoT-driven _{market environments, which recognizes the speciic impact digitization. Design Research} Modular layered architecture, _{service dominant logic}

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Wan et al. 2016 Discusses O2O business model and IoT, identifying 10 core elements _{with Analytic Network Process (ANP)} Delphi Value Net Model, ANP

Weinberger et al. 2016 Introduces the concept of high-resolution management (HRM) in IoT Theoretical paper St. Gallen Business Model _{Navigator, HRM}

Westerlund et al. 2014

Examines networked and more comprehensive ecosystem business models; focuses on the challenges that hinder the emergence of IOT

business models.

Theoretical paper Value design

Wortmann and Flüchter 2015 Discusses Internet of Things Technology and the value added by this

new technology Theoretical paper Porter and Heppelmann 2014

Zhang and Wen 2016 Propose an IoT E-business model specially designed for the IoT _{E-business and blockchain.} Theoretical paper N/A Table 1. Cont.

Table 2. Challenges on developing business models for the IoT

Categories Challenges Sources

The IoT Ecosystem

Find a value proposition to all actors involved in the ecosystem. Buchener and Uckelmann (2011)Ehret and Wirtz (2017); Leminem et al. (2015); Ghanbari et al. (2017); Saarikko, Westergren, and Blomquist (2017).

Increasing complexity in coordinating all the partners involved in

IoT.

Buchener and Uckelmann (2011); Glova et al. (2014); Leminem et al. (2015); Novales et al (2016), Porter and Heppelman (2014), Verdouw et al. (2013), Wortmann and Flüchter (2015), Bilgeri and Wortmann (2017), Ghanbari et al. (2017); Saarikko, Westergren, and Blomquist (2017).

Deine the control over hybrid solutions, the hardware, and the

software side. Ehret and Wirtz (2017)

Security in the transactions between business partners.

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Categories Challenges Sources

The Product/

service development

Higher complexity in product design - servitization and products

as-a-service demand new capabilities in traditional products. Porter and Heppelman (2014), Tesch (2016), Wortmann and Flüchter (2015)

Synchronizing the processes of software and hardware

development. Novales et al (2016), Wortmann and Flüchter (2015)

Keep simplicity of product design/user experience. Novales et al (2016)

The Value proposition

Deine the value proposition for clients – services with real aggregate value. Customer demands and expectations are still hard

to discern.

Ehret and Wirtz (2017); Leminem et al. (2015), Porter and Heppelman (2014), Burkitt, (2014), Verdouw et al. (2013); Bilgeri and Wortmann (2017), Ghanbari et al. (2017)

Privacy issues need to be considered in the value proposition. Burkitt, (2014), Ehret and Wirtz (2017); Keskin and Kennedy _{(2015); Novales et al (2016), Porter and Heppelman (2014),}

The irm’s internal

capabilities

Chance of new entrants and nontraditional competitors increase as smart, connected products become part of broader product

systems; it challenges the irm’s capabilities. Porter and Heppelman (2014)

Identify speciic organizational capabilities to support the strategic

implementation of IoT based products/services. Burkitt, (2014), Li et al (2012); Novales et al (2016), Porter and Heppelman (2014)

A realistic assessment of which capabilities should be developed

in-house and which new partners should develop is key. Burkitt, (2014), Porter and Heppelman (2014)

The Technology Infrastructure

The high complexity of technology components and IoT infrastructure.

Burkitt, (2014), Ehret and Wirtz (2017); Ju et al. (2016), Leminem et al. (2012); Novales et al (2016); Porter and Heppelman (2014), Tesch (2016), Wortmann and Flüchter (2015)

Deinition of interfaces, interoperability protocols, and standards. Burkitt, (2014), Buchener and Uckelmann (2011); Hognelid and Kalling (2014); Leminem et al. (2015), Verdouw et al. (2013); Ghanbari et al. (2017)

Large volumes of data need to be kept and analyzed Burkitt (2014)

The generation of

Revenues Forms of monetization of data are complex/diicult to deine/forecast

Tesch (2016), Verdouw et al. (2013); Bilgeri and Wortmann (2017)

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Finding valid and clear value propositions for clients also becomes more complex, because the IoT applications are related to servitization (Fleisch et al., 2014), integrating the physical and the digital worlds. It allows ofering new services related to tangible products, which increases the complexity of product development. It is also important to consider that privacy issues are crucial to the value proposition.

Considering all these challenges, a company needs to identify the capabilities needed to proit from the IoT, deciding which ones need to be developed in-house and which ones are dependent on business partners.

Finally, sources of revenue need to be rethought; for instance, the opportunities to proit from Products as Services (PaaS) and how to get value for data generated through the IoT (Buchener & Uckelmann, 2011). Most of the articles in Table 2 also discuss the complexity of the IoT due to social, regulatory and institutional elements such as policies for technology standardization, legislation regarding privacy issues and difusion of the IoT in the society as a whole.

Considering that most of the references in the literature on business models for the IoT are theoretical papers, we present, in the next sections, data from an action research project that have explored the process of business modeling for the IoT in a real company, allowing us to better understand the related challenges.

ACTION RESEARCH METHOD

One key assumption of action research is “action brings understanding” (Baskerville, 1999); in this case, we assumed that one of the best ways of understanding the process of creating a business model for the IoT, and the challenges faced in this process, was to get involved with a real company dealing with this task. In this section, we explain the method of the action research project (Avison et al., 1999; Baskerville, 1999) involving the generation of a business model for an IoT-based product (a smart door lock).

First, regarding the types of action research, Berg (2004) classify them into three main modes:

Technical/scientiic/collaborative – early advocates of action research proposed it as the application of a very rigorous scientiic method of problem- solving; the goal was to test a particular intervention based on a pre-speciied theoretical framework. In this mode, the researcher identiies a problem after collaborating with the practitioners and provides information for them.

Practical/mutual collaborative/deliberate mode – in this mode, both the researchers and the practitioners work together and collaboratively identify potential problems and issues, underlying causes and adequate interventions. This mode is more lexible and empowers the practitioners; however, the level of control and measurement is lower than in the irst mode.

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We identify the action research performed with the mode 2 (practical/mutual collaborative/ deliberate mode). The intention was to solve a practical problem (the dei nition of a business model for an IoT-based product) discussed, from the beginning, with the practitioners involved. The action plan was also discussed and approved by them. The action research was conducted from December 2014 to April 2015.

The company studied (here called “DELTA”) is a small Brazilian company founded in 2004, specialized in the development of electronic products. DELTA has a process of RD&I that focuses on projects involving hardware and software with microprocessors. The company’s vision is: “Taking innovation, comfort, and economy through technology to domestic and corporate environments.” The production line is divided in two: one with low-cost products with a traditional design: presence sensors, dimmers, and electronic buzzers; the other production line is composed of products with innovative design, including presence sensors. In addition to these products, DELTA also works with OEM (Original Equipment Manufacturer) contracts. The structure of the company consisted of one manager and two electrical engineers; a technical team with one administrative assistant and 15 employees working at the production line.

The two owners of DELTA were involved in the process of business modeling, because, as a small company, DELTA does not have administrative departments. There was no involvement of other employees, which were engaged in operational tasks. The research project was carried out by an interdisciplinary team involving researchers from management and computer science, which helped the company in the development of the technological infrastructure for their IoT-based product, and in the development of the business model for it. The action research phases are depicted in Figure 2 and described next, according to the steps suggested by Baskerville (1999).

Figure 2. Research method – steps of the action research

Table 3 shows the details of the work sessions with the company, places, and durations.

Problem identification and motivation Definition of objectives Aligment of expectations; work contract, planning Designing the Business Model Canvas for the smart

lock

Identifying and discussing the facilitators and barriers on the business modelling process AC T IO N R ES EA R C H P H A S E

Work sessions 1 and 2

Company folders, products catalogues, website; field notes of the work sessions, formal research agreement,

work plan

Results for the company and academic publications P RA C TI C AL A C TI TV ITY D ATA C O LL E C T E D / G ENER A T ED

Work sessions 3 to 6

Crossing the literature review with the action reseach results; learning specification

Work session 7

Diagnosis Action planning Action taking Evaluation Specifying learning

Literature review; field notes and recording of the work sessions, Draft of the the smart

lock Canvas

Field notes and recording of the

work session

Final version of the smart lock canvas; lessons learned with

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Table 3. Work sessions with the company

Session/Activity Place Duration (hours)

Session 1 – Understanding the company and needs University 1:50

Session 2 - Team mobilization and planning Company 1:30

Sessions 3 and 4 - Designing the business model Company 2:15

Session 5 - Designing the business model Company 0:45

Session 6 - Discussion of the technological aspects of the model University 0:55 Session 7 - Validation of the business model and evaluation of the process Company 1:45

Diagnosis (work sessions 1 and 2 at Table 3): This irst phase of research involved the

identiication of the problem and the deinition of expected results by the practitioners. It was a collaborative process; the delimitation of the problem was made during the irst two meetings with the company. In the irst meeting, the owners have made a presentation of the company and their needs. We identiied that the company had projects for products based on the IoT but did not have a formal strategic plan or business models established for them. Based on this irst interaction, we established the calendar of activities and the delimitation of the research objectives and motivations of the company. We attempted to understand the company needs and characteristics, as well as the proile of the managers involved and what could be the best form to help them in the business modeling.

Action planning (Literature search and work session 2 at Table 3): In the second meeting with

the company the research team has presented a draft of the research procedures, still attempting to understand and align the needs of practitioners with the focus of research and deine the action planning. In this second meeting, the research team has visited the company premises; a consent form was signed with the practitioners and a presentation was done by the researchers with a draft of the work plan. This plan was created after a review of the literature on business models and business models for the IoT (which was incipient at that time – 2014/2015).). The BMC was suggested as a possible framework for business modelling, because (1) it is a broad, didactic and straightforward approach to business modelling (2) it is one of the most used frameworks for business modelling, including digital businesses and the IoT (Buchener & Uckelmann, 2011; Sun et al., 2012) (3) the managers involved were acquainted with this model (although they had not applied it in their own company). The practitioners agreed that it could be an adequate framework for the process of business modeling the smart door lock. The research team and the practitioners deined together which components of the BMC would be drawn in the following work sessions.

Action taking (work sessions 3 to 6 at Table 3): in this phase, a set of meetings was held

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customers, collection of ideas and opinions; (3) Design: transforming information and ideas of the previous phases in business models prototypes that can be explored and tested. Two more steps (implementing the chosen business model and managing it) were not performed because these two last phases require a product ready to be sold in the market, something that had not happened with the smart door lock until the conclusion of this research.

Evaluating (work session 7 at Table 3): After generating the business model, a speciic meeting was conducted to evaluate this process, especially considering the facilitators and barriers. A long conversation with the practitioners was conducted to understand their views on the process of business modeling and the adequacy of the BMC as a framework to support this process.

Specifying learning: After inishing the practical meetings and evaluating the experience with

the company, the research results were crossed with the updated literature review to specify learning, as showed in the next sections. We used NVivo® as the qualitative analysis software to organize the ideas brought by the literature review and the recording and ield notes of the work sessions with the company to analyze the data according to the research questions.

ACTION RESEARCH RESULTS

During the diagnosing stage of the action research, it was clear that the company had diiculties to deine the broader business model for its IoT-based products. Thus, at irst, we decided to focus on a speciic product, the smart door lock. The main motivations to be addressed during the research were: how to create a technological and business platform to extend it for several IoT-based products, and to establish a business model suitable for the smart door lock, with the participation of current business partners of the company or not.

The company intended to develop the smart door lock using open platforms and allowing the use of Application Programming Interfaces (APIs) so that other people could develop software for other IoT-based products. The owners believed that the smart door lock is an attractive product for hotels, for example, allowing the consumption of virtual keys, and also for domestic use, permitting the entering of speciic people at speciic times (e.g., visitors, day workers, etc.).

After planning the action, considering the BMC as the framework for business modeling, a set of meetings was held to generate the model. We describe in summary how each component of the business model for the smart door lock was designed:

Customer Segment - Two customer segments for the smart door lock were identiied: domestic

users and business users. This component of the business model was evaluated by the research participants as one of the most important, and the partners emphasized that it is one of the most diicult to deine, not only for IoT-based products but for other products in the company’s portfolio. For instance, a key issue is to identify not only the target consumers’ income level but also their level of familiarity with IT use.

Value Proposition - the main values perceived by the two types of customers (domestic and

business) were raised. As an example, we can highlight security services related to the smart door lock, ease of generating copies of digital “keys”, access to traic reports, among others.

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required, as well as pages on social media where customers could comment and share their experiences with the product, helping to promote it. An app would be another way to interact with clients, who could send their impressions on the product. The product website could also ofer an online chat for support and resolution of queries and complaints in general. Another form of relationship, especially with business customers, is the participation in tradeshows and technology conferences.

Channels – one of the owners raised the importance of ofering the product in major online

marketplaces. However, there was no consensus about this move. The other owner argued that this type of product would not be sold in this kind of stores, only in those specialized in locks. So it would be interesting to use a network of partners to distribute the product, for instance, a partnership with a traditional local manufacturer of locks, which could use its commercial channels.

Key partners – during the deinition of this component one of the owners mentioned that the

irst key partner would be the University, for generating the business model, and for RD&I and development of the cloud platform for IoT-based products of the company. Other key partners are the supplier of microchips, the cloud service provider and potentially the current business partners, yet to be consulted to verify if they had the interest in entering into new lines of smart products.

Key Activities – Some key activities are the development of embedded software in the smart

door lock, the software that goes in the Cloud (middleware) and the smartphone’s app. Besides software development, there is also the application maintenance of the developed software. Other activities mentioned were the distribution of products in retail outlets or via the web, the purchase of raw materials, and product assembly, testing and packaging. During the validation session of the business model, we wondered how DELTA would develop and maintain the software, given that the company had no expertise and staf for doing this. It indicated the need of having a new partner - a company specialized in software development.  

Key resources – During the design of this component the focus was on identifying the human

resources needed, such as software and hardware development teams and an advertising and communication team, responsible for promoting and disseminating the innovative product, as well as an external consultancy for patenting the smart door lock (a product innovation, at least to the national market, at that time).

Cost Structure – costs of raw materials, labor costs, costs of the cloud services and software

providers, freight and distribution costs, taxes and costs with advertising were some of the items mentioned. Other costs are storage/warehouse, headquarters rental and commission to the sellers.

Revenue Sources – revenue sources could come from the monthly payment of services provided

via the cloud platform and extra fees for using the software. Revenues from additional services included access to a larger period of coverage for traic reports and extra keys to the smart door lock. The rental of equipment to the business segment would be a possible source of revenue, and also the sale of the smart product in OEM contracts.

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evaluated the experience of creating the business model as positive and useful, which also helped them to think and gain insights for other IoT-based products that could be created in the future.

Regarding the nine elements of the Canvas, the managers pointed out the Value Proposition and the Customer Segment as the most signiicant ones to generate the business model for the smart door lock. Another element considered as important was the key partnerships. For instance, an aspect that emerged during the research was the OEM contracts, something that has already been done by DELTA for various products in its portfolio and could be applicable also for the smart door lock. The concept of OEM is linked to areas such as supply chain, production management, and marketing and it is an important decision on the strategic positioning of a company that intends to develop IoT-based products, for example, strengthening its own brand or becoming a supplier that innovates to other company that owns the brand.

The Channel component is intrinsically associated with the Key Partners component. In the case of the smart door lock, it was necessary to clearly deine which will be the partners, and inally to get a deinition of Channels. Formerly, DELTA had attempted to keep its own sales channel, with dedicated sellers, but the result was not ideal, due to high operational costs. The lack of a solidiied brand in the market, as well as the product’s price is slightly higher than those of the competitors’ products, which made it impossible for the company to maintain the strategy of having its own sales channels.

Besides that, during the working sessions it became clear that to design IoT-based products, a well-deined technology infrastructure is necessary. It occupied most of the interaction time during the sections, mainly with the computer science researchers who were part of the research team.

One of the DELTA managers involved in the business model creation mentioned that: “[...]

What is behind it (the product), regarding technological infrastructure, it [the BMC framework] does

not say. It serves both to business modeling a high-tech product as for business modeling a bookstall. It is very generic.”

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Figure 3. The business model Canvas for the smart door lock

The discussion about the business modeling process is presented in the next section.

DISCUSSION

The i rst lesson that can be learned through the action research with DELTA is that the process of business modeling of an IoT-based product/service expands the view on the individual i rm and needs to be extended to the role the i rm wants to play in the IoT ecosystem. To decide upon what sort of product/service is going to be of ered by the i rm is related to its position in a broader value chain. For example, Ehret and Wirtz (2017) propose three main types of industrial IoT-enabled business models: (1) the provision of manufacturing assets, their maintenance, repair and operation; (2) innovative informational and analytical services that support manufacturing (e.g., based on artii cial intelligence, big data, and analytics), and (3) new services to end-users (for instance: customization by integrating end-users into the manufacturing and supply chain ecosystem). These types are similar to a typology of IoT business models pointed out by Burkitt (2014) and Saarikko, Westergren and Blomquist (2017), which highlight four main types of players in the IoT ecosystem:

VALUE PROPOSITION CHANNELS CUSTOMER RELATIONSHIPS CUSTOMER SEGMENTS REVENUE STREAMS COST STRUCTURE KEY PARTNERS CUSTOMER SEGMENTS PROPOSITION RELATIONSHIPS KEY RESOURCES RESOURCES KEY ACTIVITIES KEY ACTIVITIES B2C market -Managing home access by third parties -No cost to generate extra keys

-Managing remote keys

-Increasing home’s safety (e.g.: built-in alarms)

- Labor

- Cloud services (monthly fee) - Freight, storage, distribution - Advertising

- Fee from additional services, such as extra keys or detailed information

- Equipment rental - OEM sales - SW/HW development

teams

- Consulting services for patents and marketing - Financial resources - University

- Microprocessor’s company - Cloud computing

service provider - Current partners

- Product website/blog/chat - Social networks - Product app - Phone

- Business trade fairs

- Marketplaces - Partners’ channels

B2C market Domestic users familiar with IT and resident in big cities

B2B market Corporate users, mainly hotels and real state agencies B2B market

- Managing corporate access by third parties - Managing remote

keys to clients anytime, anywhere - No cost to generate

extra keys - Increasing

corporate safety - Development of IoT

hardware - Development of

embedded software, app and cloud - Software maintenance - Product distribution in points of sales or online - Product assembling,

testing and packaging

KEY ACTIVITIES KEY ACTIVITIES KEY ACTIVITIES

10th_{– IT}

INFRASTRUCTURE

- 3G/4G networks - Wi-fi connection - NFC

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Enablers – those irms that develop, implement and maintain the fundamental IoT technology

infrastructure. These are technology companies.

Embedders – companies that apply IoT technologies to improve their operations and optimize

their business processes (which include many manufacturing irms), but do not ofer an IoT solution for their clients.

Engagers – irms that create their own connected product/services. They design, develop, integrate, and deliver IoT services to customers. For instance, by linking a washing machine to the Internet, the appliance maker captures a wealth of data about how the device is used.

Enhancers – are the irms that devise their own value-added services, on top of the services

provided by Engagers, which are unique to the IoT. They can provide integrated services that reframe and repackage the products and services of the Engagers.

The DELTA challenge was to transform itself into an “engager” – in this case, they should develop a set of capabilities and resources such as software development to ofer services based on the data generated by the smart product. As a small irm, they could not make it on their own – the need to develop partnerships to play this new role is paramount. Even for an engineering irm such as DELTA, there is an obvious diiculty in providing all the resources to develop activities in all the areas encompassed by the IoT. The search for appropriate external partners to deliver the smart product and associated services adds complexity to the product development process and the coordination of cooperative work (as previously pointed by Buchener & Uckelmann, 2011; Glova et al., 2014; Leminem et al., 2015; Novales et al., 2016, Porter & Heppelman, 2014, Verdouw et al., 2013, Wortmann & Flüchter, 2015).

Another valuable insight from the DELTA experience is that traditional products (such as door locks) can be completely rethought through servitization, but it is a big challenge to deine the services that actually generate real value for consumers (as also highlighted by Ehret & Wirtz, 2017; Leminem et al., 2015, Porter & Heppelman, 2014 and Verdouw et al., 2013).

In the case of the smart door lock, the convenience generated by the services provided, such as permitting the entering of speciic people at speciic times (e.g., visitors, day workers, etc.), or the provision of security information and reports on peoples’ circulation are very important. Experimenting on speciic pilot projects is important because the IoT adoption is not reaching a mass market yet; there are no killing applications of it until now (Buchener & Uckelmann, 2011; Ju et al., 2016; Leminem et al., 2015, Verdouw et al., 2013).

Another aspect that became clear in the work with DELTA is that the complexity of the IoT technologies deeply afects the process of business modeling; the technology infrastructure must be clearly deined since it changes the way the value proposition can be designed and delivered. Technology deinitions will also afect the selection of key partners and the revenue models.

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It is also necessary to rethink the value capture for IoT-based products/services. Once that the IoT increases the opportunities for servitization, exemplary business model patterns can include Rent instead of Buy, Subscription, Freemium, Razor and Blade and Add-on (Fleisch et al., 2014). Assets that have not traditionally been viewed as such, for example, traic (i.e. visitors to a website), content and eyeballs (i.e. users seeing adverts) can generate new revenues, but still are poorly explored by irms (Ng & Wakenshaw, 2017).

DELTA should deine the revenue model from services and information provided by the smart door lock for customers, for instance, through the provision of additional keys or granting access to data for a larger period. Regarding these services, one key issue is privacy, because IoT enables the collection of vast amounts of privacy-sensitive data (Derikx, De Reuver, & Kroesen, 2015), for instance, in the case of the smart door lock, data on the circulation of people in private and public spaces.

CONCLUSIONS

This article aimed to investigate what are the main elements to be considered to create a business model for IoT-based products/services and what are the key challenges faced in this process.

We contribute to the literature by analyzing the state of art on business modeling for the IoT, and also by confronting this knowledge with a real experience of creating a business model for a smart product. The research results reveal that “generic” business model frameworks, such as the Business Model Canvas (BMC) can help a company to design its business model for the IoT, but still lacks some speciic areas (such as IT infrastructure) that need to be considered to encompass the complexity of this process. For instance, the irm needs to think about its role and the business model considering the IoT ecosystem, being aware that the process of developing solutions in this new platform will demand strong cooperation in a broader value chain. The deinitions regarding the IoT technological infrastructure deserve special attention when designing the business model.

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Challenges Practical recommendations

Ecosystem

The business model needs to be thought considering the IoT ecosystem and not only the individual irm

The irm needs to deine what role it will play in the IoT ecosystem (for instance: Enabler, Embedder, Engager; Enhancer)

Product/

service development

It is fundamental to understand that the level of complexity in product development increases; partnerships are essential to deal with the complexity

Several channels to interact with customer and monitoring their user experience for constant improvements are important

Value proposition

Is important to deine clear value propositions considering customers’ needs, proile and level of familiarity with the technology

The convenience provided by the services related to smart products is a key aspect Experimenting on speciic pilot projects of IoT-based products is a good way of learning and understanding the complexity of business modeling for the IoT

It is essential to consider privacy issues related to the data services provided by smart products

Firms’

Internal capabilities

The irm needs to make a realistic assessment of its assets and capabilities to develop the IoT-based product/service

It needs to reevaluate what are the potential competitors and partners in the ofering of smart products

Technology Infrastructure

This element is underestimated in most of the “generic” business models frameworks and needs to be carefully considered in business modeling IoT applications because it strongly inluences the value proposition and the forms of value capture

The irm needs to develop technology partnerships and the capacity to manage them Interoperability is essential and an open platform can be generative and proitable in new business models based on the IoT

Revenues The range of possibilities of revenue generation related to smart products can be explored, including value captured through data services and the provision of lexible, additional, on- demand services

As research limitations, we can highlight the small size of the researched company and the short period of research. We also carried out only 3 of the 5 steps to generate a business model using the Business Model Canvas since the core product of this process (the smart door lock) was in the prototyping stage. The high degree of involvement of the researchers with the company also needs to be considered.

For future studies, we suggest the creation and the empirical testing of speciic frameworks for the generation of business models for the IoT. These frameworks should consider the idiosyncrasies of the IoT platform and its level of complexity, as well as the challenges for business modeling for IoT as discussed in this article. The need of expansion of the BMC in the DELTA study signals that we need improved frameworks which can include new areas in the business models and, especially, to connect the areas and explore the interdependencies between them. Finally. it is important to advance the discussion of the concept of IoT ecosystems (and the diferent roles irms can play on it), as well as the servitization enhanced by the IoT, issues that are clearly highlighted in this research.

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